Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
Reusable Components for Knowledge Modelling: Case Studies in Parametric Design Problem Solving
Reusable Components for Knowledge Modelling: Case Studies in Parametric Design Problem Solving
Designing and Evaluating E-Business Models
IEEE Intelligent Systems
The Knowledge Engineering Review
Computers in Industry - Special issue: Process/workflow mining
A Comprehensive and Automated Approach to Intelligent Business Processes Execution Analysis
Distributed and Parallel Databases
A semantic approach to monitor business process
Communications of the ACM - The semantic e-business vision
ICEBE '05 Proceedings of the IEEE International Conference on e-Business Engineering
Real Time Business Intelligence for the Adaptive Enterprise
CEC-EEE '06 Proceedings of the The 8th IEEE International Conference on E-Commerce Technology and The 3rd IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services
Semantic Business Process Management: Scaling Up the Management of Business Processes
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
SENTINEL: a semantic business process monitoring tool
OBI '08 Proceedings of the first international workshop on Ontology-supported business intelligence
Business process management: a survey
BPM'03 Proceedings of the 2003 international conference on Business process management
An outlook on semantic business process mining and monitoring
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
A core ontology for business process analysis
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
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Business Process Management (BPM) aims to support the whole life-cycle necessary to deploy and maintain business processes in organisations. Crucial within the BPM life-cycle is the analysis of deployed processes. Analysing business processes requires computing metrics that can help determining the health of business activities and thus the whole enterprise. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. In this paper we argue and show how the use of Semantic Web technologies can increase to an important extent the level of automation for analysing business processes. We present a domain-independent ontological framework for Business Process Analysis (BPA) with support for automatically computing metrics. In particular, we define a set of ontologies for specifying metrics. We describe a domain-independent metrics computation engine that can interpret and compute them. Finally we illustrate and evaluate our approach with a set of general purpose metrics.